Ship Detection via Superpixel-Random Forest Method in High-Resolution SAR Images

2019 ◽  
pp. 702-707
Author(s):  
Xiulan Tan ◽  
Zongyong Cui ◽  
Zongjie Cao ◽  
Rui Min
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Sar Images ◽  
Ship Detection ◽  
Random Forest Method

Ship Detection With Superpixel-Level Fisher Vector in High-Resolution SAR Images

2020 ◽  
Vol 17 (2) ◽  
pp. 247-251 ◽  
Author(s):  
Huiping Lin ◽  
Hang Chen ◽  
Kan Jin ◽  
Liang Zeng ◽  
Jian Yang
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
Ship Detection ◽  
Fisher Vector

An Improved Algorithm for Ship Detection from the High-Resolution SAR Images

2014 ◽  
Vol 1044-1045 ◽  
pp. 1040-1044
Author(s):  
Qing Ping Wang ◽  
Hong Zhu ◽  
Wei Wei Wu ◽  
Chang Zhu ◽  
Nai Chang Yuan
Keyword(s):  
High Resolution ◽  
Region Of Interest ◽  
Speckle Noise ◽  
False Alarms ◽  
Constant False Alarm Rate ◽  
Sar Images ◽  
Ship Detection ◽  
Whole Process ◽  
Preliminary Extraction ◽  
Improved Algorithm

An improved algorithm for ship detection from the high-resolution synthetic aperture radar (SAR) images is proposed in this paper. In this algorithm, we firstly utilize the image pre-processing step to suppress the speckle noise. Then, the ship ROIs (Region of Interest) are obtained based on MSER (Maximally Stable Extremal Region) method, which enables preliminary extraction of ship candidates. Finally, an improved CFAR (Constant False Alarm Rate) detector is designed for accurate detection with the purpose of accelerating the whole process and decreasing false alarms. The experimental results show that this method can achieve effective ship detection in high-resolution SAR images. The process of ship detection is also accelerated which is in favour of the project realization.

scholarly journals Two-Parameter CFAR Ship Detection Algorithm Based on Rayleigh Distribution in SAR Images

2021 ◽  
Author(s):  
Ruochen Wu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Microwave Remote Sensing ◽  
Rayleigh Distribution ◽  
Global Ocean ◽  
Distribution Model ◽  
Sar Image ◽  
Sar Images ◽  
Ship Detection ◽  
Two Parameter

Synthetic Aperture Radar (SAR) is an active type of microwave remote sensing. Using the microwave imaging system, remote sensing monitoring of the land and global ocean can be done in any weather conditions around the clock. Detection of SAR image targets is one of the main needs of radar image interpretation applications. In this paper, an improved two-parameter CFAR algorithm based on Rayleigh distribution and morphological processing is proposed to perform ship detection and recognition in high resolution SAR images. Through simulation experiments, comprehensive study of the two algorithms for high resolution SAR image target detection is achieved. Finally, the results of ship detection experiments are compared and analyzed, and the effects of detection are evaluated according to the Rayleigh distribution model and algorithms.

Brain-Inspired Fast Saliency-Based Filtering Algorithm for Ship Detection in High-Resolution SAR Images

2021 ◽  
pp. 1-9
Author(s):  
Panpan Zhang ◽  
Haibo Luo ◽  
Moran Ju ◽  
Miao He ◽  
Zheng Chang ◽  
...  
Keyword(s):  
High Resolution ◽  
Sar Images ◽  
Filtering Algorithm ◽  
Ship Detection
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